A Gentle Introduction to Maximum Likelihood Estimation and Maximum A Posteriori Estimation

<p>In 2018-19 season, Liverpool FC won 30 matches out of 38 matches in Premier league. Having this data, we&rsquo;d like to make a guess at the probability that Liverpool FC wins a match in the next season.</p> <p>The simplest guess here would be&nbsp;<em>30/38 = 79%</em>, which is the best possible guess based on the data. This actually is an estimation with&nbsp;<strong>MLE</strong>&nbsp;method.</p> <p>Then, assume we know that Liverpool&rsquo;s winning percentages for the past few seasons were around 50%. Do you think our best guess is still 79%? I think some value between 50% and 79% would be more realistic, considering the prior knowledge as well as the data from this season. This is an estimation with&nbsp;<strong>MAP</strong>&nbsp;method.</p> <p><a href="https://towardsdatascience.com/a-gentle-introduction-to-maximum-likelihood-estimation-and-maximum-a-posteriori-estimation-d7c318f9d22d"><strong>Learn More</strong></a></p>